Noise is a common problem in digital images, and digital signal processing (DSP) algorithms may be used to decrease noise in digital images. For example, the noise may be random, unwanted fluctuations in pixel values that make the image look grainy. There are several de-noising algorithms currently available that aim to decrease digital image noise; however these algorithms tend to have problems separating noise and data. This is especially problematic when a digital image has fine details in a low contrast region.
Most de-noising algorithms tend to perform well on uniform areas in a digital image, but typically have substantial problems eliminating noise on edges and contours in a digital image, and in detail-rich areas of a digital image, without blurring the digital image. Here, detail-rich areas may include closely situated pixels that exhibit varying contrast levels. The problems of eliminating noise may lead to a loss of information.
What is needed are techniques that solve the issues described above without adversely affecting other characteristics of an image.